A network pharmacology approach to assess the comparative pharmacodynamics of pharmaceutical excipient trehalose in human, mouse and rat

Abstract

Background: Trehalose is used as a pharmaceutical excipient due to its several desirable pharmacokinetic and historically evident safety features. However, information on the pharmacodynamic properties of trehalose is lacking. Hence this study evaluated the comparative pharmacodynamic properties of trehalose using a network pharmacology approach. Materials and methods: The specific targets of trehalose in human, mouse and rat were identified from the SwissTargetPrediction database, categorised and compared. The expression profile and subcellular localisation of the targets of trehalose in human was identified and correlated with the affinity of trehalose to these targets to assess its impact on the pharmacodynamic properties of trehalose. The affinity of trehalose to its metabolising enzyme in human, mouse, and rat was assessed by molecular docking and compared. Results: A significant difference in the target categories and target types of trehalose was observed in human, mouse, and rat. The affinity of trehalose to human (66.03 +/- 5.1 microM), rat (102.53 +/- 11.3 microM) and mouse (42.07 +/- 5.3 microM) trehalase was significantly different. Family A G protein coupled receptors were identified as the major target category of trehalose and cyclin dependent kinase 1 was observed as the high affinity target of trehalose in human and mouse. The correlation of target expression and affinity indicated minimal pharmacodynamic influence under physiological conditions. Conclusion: This study reports the selective targets of trehalose relevant to drug discovery and development protocols and highlights the limitations of rodent models in translating pharmacodynamic analysis of trehalose for development of human therapeutics.

Network pharmacology of xylazine to understand Its health consequences and develop mechanistic based remediations

“…To identify the most optimal approach to antagonise the xylazine pharmacology, in this study most know alpha-2 adrenergic receptor-antagonists (yohimbine, chlorpromazine, phentolamine, mianserine, spiperone, prazosin, alprenolol, propranolol, pindolol, atipamezole, dexmedetomidine and tolazoline) and CNS stimulants (4-aminopyridine, doxapram and caffeine) which are approved for clinical use were assessed for their affinity against all high affinity targets of xylazine as mentioned above. [13][14][15] A heat map of the affinity ratio values of the agonist (xylazine) / antagonist was generated to identify the most optimal drug to antagonise the xylazine pharmacology.…”

“…The isomeric SMILES sequence of xylazine (CC1=C(C(=CC=C1)C)NC2=NCCCS2) obtained from the PubChem database was inputted into the SwissTargetPrediction server (http://www.swisstargetprediction.ch/) and STITCH database (http://stitch-db.org/) to identify the targets specific to homo sapiens. 13-15…”

“…The specific interaction sites, binding pocket sequence, EC 50 values, and the number of hydrogen bonds formed during receptor-ligand interaction were also estimated as reported previously. 13-15…”

“…The isomeric SMILES sequence of xylazine (CC1=C(C(=CC=C1)C)NC2=NCCCS2) obtained from the PubChem database was inputted into the SwissTargetPrediction server (http://www.swisstargetprediction.ch/) and STITCH database (http://stitchdb.org/) to identify the targets specific to homo sapiens. [13][14][15] The pharmacokinetic parameters of xylazine were assessed using the SwissADME server and data reported in the literature. The observed dosage (mg/day), plasma concentration achieved (µM) and volume of distribution (L) was trichotomized into low, medium, and high categories.…”

Comparative network pharmacology of artificial sweeteners to understand Its health consequences

“…28 The Uniprot database (https://www.uniprot.org/) was used to obtain the protein sequence of each individual target of the ASwt, and Yuel tool (https://dokhlab.med.psu.edu/ cpi/#/YueL) and Autodock Vina 1.2.0 were used to predict the affinity between the sweeteners and each of their potential targets as described before. [29][30][31][32][33] The targets were then classified into various functional groups, to assess the selectivity of each ASwt to any specific functional group(s).…”